Responsible Robotics and Responsibility Attribution

This paper stresses the centrality of human responsibility as the necessary foundation for establishing clear robotics policies and regulations; responsibility not on the part of a robot’s hardware or software, but on the part of the humans behind the machines—those researching and developing robotics. Simply put, we need responsible robotics. Responsible robotics is a term that has recently ‘come into vogue’, yet an understanding of what responsible robotics means is still in development. In light of both the complexity of development (i.e. the many hands involved) and the newness of robot development (i.e. few regulatory boards established to ensure accountability), there is a need to establish procedures to assign future responsibilities among the actors involved in a robot’s development and implementation. The three alternative laws of responsible robotics by Murphy and Wood play a formidable contribution to the discussion; however, they repeat the difficulty that Asimov introduced, that is, laws in general, whether they are for the robot or for the roboticist, are incomplete when put into practice. The proposal here is to extend the three alternative laws of responsible robotics into a more robust framework for responsibility attribution as part of the responsible robotics goal. This framework requires making explicit various factors: the type of robot, the stage of robot development, the intended sector of use, and the manner of robot acquisition. With this in mind, one must carefully consider the scope of the ethical issue in question and determine the kind of responsibility attributed to said actor(s).

Differences Between Natural and Artificial Cognitive Systems

This chapter identifies the differences between natural and artifical cognitive systems. Benchmarking robots against brains may suggest that organisms and robots both need to possess an internal model of the restricted environment in which they act and both need to adjust their actions to the conditions of the respective environment in order to accomplish their tasks. However, computational strategies to cope with these challenges are different for natural and artificial systems. Many of the specific human qualities cannot be deduced from the neuronal functions of individual brains alone but owe their existence to cultural evolution. Social interactions between agents endowed with the cognitive abilities of humans generate immaterial realities, addressed as social or cultural realities. Intentionality, morality, responsibility and certain aspects of consciousness such as the qualia of subjective experience belong to the immaterial dimension of social realities. It is premature to enter discussions as to whether artificial systems can acquire functions that we consider as intentional and conscious or whether artificial agents can be considered as moral agents with responsibility for their actions.

AI Nuclear Winter or AI That Saves Humanity? AI and Nuclear Deterrence

Nuclear deterrence is an integral aspect of the current security architecture and the question has arisen whether adoption of AI will enhance the stability of this architecture or weaken it. The stakes are very high. Stable deterrence depends on a complex web of risk perceptions. All sorts of distortions and errors are possible, especially in moments of crisis. AI might contribute toward reinforcing the rationality of decision-making under these conditions (easily affected by the emotional disturbances and fallacious inferences to which human beings are prone), thereby preventing an accidental launch or unintended escalation. Conversely, judgments about what does or does not suit the “national interest” are not well suited to AI (at least in its current state of development). A purely logical reasoning process based on the wrong values could have disastrous consequences, which would clearly be the case if an AI-based machine were allowed to make the launch decision (this virtually all experts would emphatically exclude), but grave problems could similarly arise if a human actor relied too heavily on AI input.

Humans Judged by Machines: The Rise of Artificial Intelligence in Finance, Insurance, and Real Estate

There are opportunities but also worrisome trends as AI is applied in finance, insurance, and real estate. In these domains, persons are increasingly assessed and judged by machines. The financial technology (Fintech) landscape ranges from automation of office procedures, to new approaches for storing and transferring value, to the granting of credit. The Fintech landscape can be separated into “incrementalist Fintech” and “futurist Fintech.” Incrementalist Fintech uses data, algorithms, and software to complement professionals who perform traditional tasks of existing financial institutions. It promises financial inclusion, but this inclusion can be predatory, creepy, and subordinating. These forms of financial inclusion undermine their solvency, dignity, and political power of borrowers. Futurist Fintech’s promoters claim to be more equitable, but are likely to falter in their aspiration to substitute technology for key financial institutions. When used to circumvent or co-opt state monetary authorities, both incrementalist and futurist Fintech expose deep problems at the core of the contemporary digitization of finance.

AI/Robotics and the Poor

Artificial intelligence and robotics (AI/R) have the potential to greatly change livelihoods. Information on how AI/R may affect the poor is scarce. This chapter aims to address this gap in research. A framework is established that depicts poverty and marginality conditions of health, education, public services, work, small businesses, including farming, as well as the voice and empowerment of the poor. This framework identifies points of entry of AI/R, and is complemented by a more detailed discussion of the way in which changes through AI/R in these areas may relate positively or negatively to the livelihood of the poor. Context will play an important role determining the AI/R consequences for the diverse populations in poverty and marginalized populations at risk. This chapter calls for empirical scenarios and modelling analyses to better understand the different components in the emerging technological and institutional AI/R innovations and to identify how they will shape the livelihoods of poor households and communities.

A Human Blueprint for AI Coexistence

The positive coexistence of humans and AI is possible and needs to be designed as a system that provides for all members of society, but one that also uses the wealth generated by AI to build a society that is more compassionate, loving, and ultimately human. It is incumbent on us to use the economic abundance of the AI age to foster the values of volunteers who devote their time and energy toward making their communities more caring. As a practical measure, to protect against AI/robotics’ labor saving and job displacement effects, a “social investment stipend” should be explored. The stipend would be given to those who invest their time and energy in those activities that promote a kind, compassionate, and creative society, i.e., care work, community service, and education. It would put the economic bounty generated by AI to work in building a better society, rather than just numbing the pain of AI-induced job losses.

Robots and Rights: Reviewing Recent Positions in Legal Philosophy and Ethics

Controversies about the moral and legal status of robots and of humanoid robots in particular are among the top debates in recent practical philosophy and legal theory. As robots become increasingly sophisticated, and engineers make them combine properties of tools with seemingly psychological capacities that were thought to be reserved for humans, such considerations become pressing. While some are inclined to view humanoid robots as more than just tools, discussions are dominated by a clear divide: What some find appealing, others deem appalling, i.e. “robot rights” and “legal personhood” for AI systems. Obviously, we need to organize human–robot interactions according to ethical and juridical principles that optimize benefit and minimize mutual harm. Avoiding disrespectful treatment of robots can help to preserve a normative basic ethical continuum in the behaviour of humans. This insight can contribute to inspire an “overlapping consensus” as conceptualized by John Rawls in further discussions on responsibly coordinating human/robot interactions.

Friendship Between Human Beings and AI Robots?

In this chapter the case for potential Robophilia is based upon the positive properties and powers deriving from humans and AI co-working together in synergy. Hence, Archer asks ‘Can Human Beings and AI Robots be Friends?’ The need to foreground social change for structure culture and agency is being stressed. Human enhancement speeded up with medical advances with artificial insertions in the body, transplants, and genetic modification. In consequence, the definition of ‘being human’ is carried further away from naturalism and human essentialism. With the growing capacities of AI robots the tables are turned and implicitly pose the question, ‘so are they not persons too?’ Robophobia dominates Robophilia, in popular imagination and academia. With AI capacities now including ‘error-detection’, ‘self-elaboration of their pre-programming’ and ‘adaptation to their environment’, they have the potential for active collaboration with humankind, in research, therapy and care. This would entail synergy or co-working between humans and AI beings.

Impact of AI/Robotics on Human Relations: Co-evolution Through Hybridisation

This chapter examines how the processes of human enhancement that have been brought about by the digital revolution (including AI and robotics, besides ICTs) have given rise to new social identities and relationships. The central question consists in asking how the Digital Technological Matrix, understood as a cultural code that supports artificial intelligence and related technologies, causes a hybridisation between the human and the non-human, and to what extent such hybridisation promotes or puts human dignity at risk. Hybridisation is defined here as entanglements and interchanges between digital machines, their ways of operating, and human elements in social practices. The issue is not whether AI or robots can assume human-like characteristics, but how they interact with humans and affect their social identities and relationships, thereby generating a new kind of society.

Designing Robots for the Battlefield: State of the Art

There is currently a global arms race for the development of artificial intelligence (AI) and unmanned robotic systems that are empowered by AI (AI-robots). This paper examines the current use of AI-robots on the battlefield and offers a framework for understanding AI and AI-robots. It examines the limitations and risks of AI-robots on the battlefield and posits the future direction of battlefield AI-robots. It then presents research performed at the Johns Hopkins University Applied Physics Laboratory (JHU/APL) related to the development, testing, and control of AI-robots, as well as JHU/APL work on human trust of autonomy and developing self-regulating and ethical robotic systems. Finally, it examines multiple possible future paths for the relationship between humans and AI-robots.